Modern data centers often include a large number of hosts, or nodes, that may operate on a large amount of data. Because this data is often spread out across a large number of nodes, indexing and searching operations can be difficult to perform in an effective manner. MapReduce functions are one way to process this large amount of data that is spread across a large number of nodes. MapReduce functions may include two phases. The first phase (e.g., the “mapping” phase) performs filtering and sorting operations on the data. The second phase (e.g., the “reduce” phase) performs consolidation operations on the filtered data.